Agentic Ai Engineer (Insurance and Agentic Workflows) - Boston, MA

Sourced from movojobs.com

A leading insurance organization is hiring an Agentic AI Engineer to design, build, and deploy production-grade AI agents and multi-step agentic workflows that automate complex business processes. This hands-on role blends software engineering, applied AI, and business collaboration, with roughly 80% hands-on engineering and 20% design and strategy. You will build reusable frameworks, integrate agents with enterprise systems, and establish testing, evaluation, and governance practices for AI systems.

• Design, build, and deploy AI agents and multi-step agentic workflows
• Develop reusable frameworks, components, and engineering patterns
• Build backend services using Python and FastAPI
• Integrate AI agents with enterprise applications, APIs, data platforms, and external services
• Establish testing methodologies, evaluation frameworks, and continuous improvement processes
• Implement governance controls, guardrails, human-in-the-loop workflows, monitoring, and audit capabilities
• Prototype rapidly and scale successful implementations into production
• Collaborate with technical and business stakeholders to identify high-value AI opportunities

• Bachelor's degree in CS, Engineering, or related quantitative field with 7+ years of software engineering, ML, or data engineering experience (or Master's with 5+ years)
• 2+ years of hands-on experience building LLM-based applications
• Experience deploying at least one production agentic AI system used by end users
• Strong Python programming and software engineering skills
• Experience building and consuming APIs in enterprise environments
• Understanding of testing, debugging, version control, and software delivery best practices
• Hands-on experience with agent frameworks or SDKs, with LangGraph strongly preferred
• Experience with model APIs and managed AI platforms such as Amazon Bedrock
• Experience evaluating LLM applications using testing frameworks, metrics, datasets, and automated assessments
• Understanding of AI security, reliability, governance, and responsible deployment
• Strong communication and stakeholder management skills

• Insurance industry experience, particularly underwriting or claims operations
• AWS cloud experience
• Containerization technologies and CI/CD pipelines
• Knowledge of Retrieval-Augmented Generation (RAG)
• Experience with context engineering and structured output frameworks
• Integrating AI agents via APIs and MCP architectures
• Mentoring engineers and influencing AI engineering best practices
• Building monitoring, observability, and cost management solutions for AI systems